Indicators and methods for noninvasive determination of fluid status of patients are important for monitoring of the condition of critical care patients. In many critical care settings clinicians must decide whether patients should be given intravenous fluid boluses and other therapies to improve perfusion. Excessive fluid can be damaging by impairing lung function when it decreases oxygen delivery to tissues and contributes to organ failure. Insufficient fluid can result in insufficient tissue perfusion which can also contribute to organ failure. Determining the best course of fluid therapy for a given patient is difficult and clinicians have few clinical signs to guide them.
Fluid administration in hemodynamically unstable patients is often a major challenge when it comes to measuring hemodynamic parameters in real time. Correct clinical assessment of hypovolemia is difficult, as is the decision to undertake fluid resuscitation as the initial treatment strategy. Specifically, it is very difficult to predict whether a hemodynamically unstable patient will respond to fluid therapy with an increase in stroke volume (SV) and cardiac output (CO). Moreover, fluid overload can cause significant pulmonary or cardiac dysfunction, whereas fluid insufficiency may cause tissue damage resulting in vital organ dysfunction. A patient's fluid responsiveness is the major and most important determinant to assess the adequacy of fluid resuscitation therapy and to ensure optimal cardiac performance and organ perfusion.
There are several dynamic parameters that can be used to assess fluid responsiveness from arterial blood pressure (ABP) and in some cases from plethysmogram signals. Several bedside indicators of ventricular preload have been used as predictors of fluid responsiveness. Right arterial pressure (RAP) and pulmonary artery occlusion pressure (PAOP) are commonly used in the intensive care unit (ICU) when deciding to administer fluids. Other bedside indicators of ventricular preload include right ventricular end diastolic volume (RVEDV) and left ventricular end diastolic area (LVEDA) measured with transesophageal echocardiography. Several studies and case reports have shown, however, that these static indicators based on cardiac filling pressures many have poor predictive value and often fail to give adequate information about fluid responsiveness.
Published studies have confirmed the clinical significance of monitoring the variations observed in left ventricular stroke volume that result from the interaction of the cardiovascular system and the lungs under mechanical ventilation. These stroke volume variations (SVV) are caused by the cyclic increases and decreases in the intrathoracic pressure due to the mechanical ventilation, which lead to variations in the cardiac preload and afterload. SVV has recently been extensively investigated and several studies have shown the usefulness of using SVV as predictor of fluid responsiveness in various clinical situations. Several other parameters based on SVV have been found to be useful as well. In particular, systolic pressure variation (SPV) with its delta-Up and delta-Down components has been found to be a very useful predictor of fluid responsiveness. SPV is based on the changes in the arterial pulse pressure due to respiration-induced variations in stroke volume. Yet another parameter that has recently been investigated and shown to be a valid indicator of fluid responsiveness is the pulse pressure variation (PPV).
Dynamic indicators based on cardiopulmonary interactions are accurate predictors of fluid responsiveness in mechanically ventilated patients under general anesthesia. Published studies have demonstrated that respiratory variations in arterial pulse pressure (PPV) were able to predict fluid responsiveness with good sensitivity and specificity in this setting.
The PPV index is a measure of the respiratory effect on the variation of systemic arterial blood pressure in patients receiving full mechanical ventilation. It is a dynamic predictor of increases in cardiac output due to an infusion of fluid. Published studies have demonstrated that PPV is one of the most sensitive and specific predictors of fluid responsiveness. Specifically, PPV has been shown to be useful as a dynamic indicator to guide fluid therapy in different patient populations receiving mechanical ventilation. For instance, PPV was found to exhibit better performance as a predictor of fluid responsiveness in patients before off-pump coronary artery bypass grafting than standard static pre-load indexes. PPV has also been shown to be useful for predicting and assessing the hemodynamic effects of volume expansion and a reliable predictor of fluid responsiveness in mechanically ventilated patients with acute circulatory failure related to sepsis. Another study concluded that PPV can be used to predict whether or not volume expansion will increase cardiac output in postoperative patients who have undergone coronary artery bypass grafting. A critical review of studies investigating predictive factors of fluid responsiveness in intensive care unit patients concluded that PPV and other dynamic parameters should be used preferentially to static parameters to predict fluid responsiveness.
The standard method for calculating PPV often requires simultaneous recording of arterial and airway pressure. Pulse pressure (PP) is calculated on a beat-to-beat basis as the difference between systolic and diastolic arterial pressure. Maximal PP (PPmax) and minimal PP (PPmin) are calculated over a single respiratory cycle, which is determined from the airway pressure signal. Pulse pressure variations PPV are calculated in terms of PPmax and PPmin and expressed as a percentage,
                              PPV          ⁡                      (            %            )                          =                  100          ×                                                    PP                max                            -                              PP                min                                                                    (                                                      PP                    max                                    +                                      PP                    min                                                  )                            /              2                                                          (        1        )            